A Personalized Future, with Mike Barclay of MoEngage

Personalization in marketing is nothing new; since the dawn of the internet, brands have been able to customize messaging to specific groups or even individuals. However, we haven’t always used this engagement superpower for good. Many brands have been guilty of getting a little too personal and creeping out their customers in the process. But today’s guest says there’s a bright future for personalization as a cornerstone to modern marketing. Mike Barclay of MoEngage joined the pod to discuss the highs and lows of personalization, and what brands born before the dawn of the internet can do to get in on the personalization game.

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QR Codes: Are they Back for Real This Time?

QR Codes are an extension of the barcode, and were first introduced as a way for manufacturers to scan larger amounts of data quickly. By 2011, retailers and tradeshows were able to take advantage of smartphone technology to utilize QR codes in their inventories, badging, and check-ins — and slowly there emerged consumer usage in the form of online offers.
The process, however, was clunky and involved third-party app software to get QR Codes to work. Fast forward to 2020, when the COVID-19 pandemic raged, and the need for contactless interaction became paramount. It was during this time that QR Code technology could now exist on everything from packaging to OOH signage, and with a simple hover of a smartphone’s camera send consumers to microsites, check-in pages, and offers.
This has allowed marketers to take advantage of QR Codes in ways previously unthought of; however, like most technologies, there are privacy and safety issues to be aware of — and the current speed and ease of QR Code usage means large untapped potential for marketers in the future as well. Read on to see how marketers are using them and addressing issues with QR Codes.

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Pulse Issue 28

SEO in 2021: To Keyword Clusters, and Beyond!

April 2021

By Josch Chodakowsky, Senior Manager, Research & Innovation at Ask the Expert
By Josch Chodakowsky, Research Manager at Ask the Expert
SEO was a lot simpler in a less-crowded marketplace; you could optimize by keyword for your product, industry, or customer demographics and watch your traffic grow. In 2021, however, not only is the online space left with little metaphorical keyword elbow room, but search engines have gotten smarter to keep up with consumer demand. People search more conversationally due to voice assistants like Alexa and Siri, and AI-powered chatbots learn more as they’re being searched, which also contributes to a natural semantic search style. If marketers want to make sure their SEO efforts are being noticed, there are several ways to do this, all of which embrace this more casual way of searching consumers are employing – “long-tail keywords,” those with fewer search results but a higher conversion rate; “keyword clusters,” which group product identifiers that can single out your brand;  “natural language processing (or NLP)” which rely on qualifiers like “what” and “where” to make a search less-robotic, and the overall conversational style that voice search and chatbots have made more prominent as of late. The resources collected here discuss how marketers can utilize each of these strategies to stand out in the digital crowd.
Search results pages are crowded these days, with everyone vying for a spot at the top. This means that if you want good placement for a simple, generic search term, you're going to face a lot of competition. That's why, when conducting keyword research, it's important to target highly-specific keywords — these are known as long-tail keywords. Long-tail keywords are usually well-thought-out queries in the form of questions, phrases, and sentences. They’re typically three or more words long. The term “long-tail” refers to the “long tail” of a search’s demand curve. As queries around a topic become more specific, the search volume decreases while the likelihood of conversion increases. This creates a skewed distribution:
Long-tail keywords are especially valuable in retail because their high specificity indicates high purchase intent. Also, it's much easier to rank for long-tail keywords versus their more general counterparts, as long-tail keywords comprise 92 percent of all keywords typed into search engines. This post from HubSpot provides examples of strategies for finding these keywords, as well as some tools that exist to help you uncover them.
Over the last few years, Google’s engineering team has directed its focus towards natural language processing (NLP) and a deeper understanding of how on-page content interrelates. Neural matching helped Google understand synonyms, and BERT helped Google understand tricky prepositions. With every core update, Google gets more literary. But despite Google getting smarter, many site owners still optimize their websites with only a few keyword targets in mind. This is an outdated practice, especially when we know our landing pages often end up ranking for hundreds of keywords anyway. As Google’s NLP capabilities continue to improve, our on-page SEO strategy also needs to evolve to reflect those advancements in search, and keyword clustering is the answer. Keyword clusters are groups of keywords that represent searchers with similar purchase intent. Let’s say your brand sells linen curtains. If you only try to rank for the first keyword, you end up limiting your market share. If you instead get your web page ranking for your primary keyword and the long-tail variants and related subtopics, your page will often end up ranking for 10 to 20 times the amount of keywords and pick up significantly more traffic.
Content Marketing Company BrightSpot explains that “Search engines like Google and Bing are working to deliver search results that respond more accurately to questions phrased in conversational language. The search language characterized by robotic, keyword-heavy phrasing (“Empire State height”) may have satisfied our needs until now, but meeting complex requests phrased in our natural language will be key to maintaining optimal search performance in the future. Search is trending in the natural language direction due to several key shifts:
  • Search engine evolution means users expect perfect results on their first attempt.
  • Search technology has advanced enough to be able to handle complex reasoning.
  • The rise of voice-activated technology.
In other words, the trend toward natural language underlying future search parameters means we’re teaching computers how to think like us. In turn, publishers stand to benefit from the advancing work in this area to make their content more effective.”
Keywords represent the tip of the iceberg when it comes to understanding consumer intent; using AI-powered chatbots, conversational data that occurs over messaging channels like Facebook Messenger and Instagram Messaging can give businesses a deeper understanding of what consumers want. Search Engine Watch discusses how conversational marketing platforms use natural language processing (NLP) and artificial intelligence (AI) to guide customers through the buying funnel. A robust conversational marketing platform makes it possible for companies to build chatbots that engage and convert customers on the websites, apps, and social platforms where people spend their time.
Are you an ANA member with a research request? Contact Ask the Expert to submit your question.

About ANA Marketing Futures

Knowing that marketers are increasingly challenged in their efforts to keep up with the latest trends and technologies, the Association of National Advertisers (ANA) tasked itself with creating a program designed to help marketers anticipate—and prepare for—the future of marketing.

 

ANA Marketing Futures is what emerged. With a focus on innovative topics and emerging trends, ANA Marketing Futures provides resources that will influence and inform via member cases, research studies, and insight from industry innovators. Check back often to learn about emerging trends and become inspired to take steps toward the growth of your business.

 

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